from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE 		=      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE 		=      {
    """facebook/levit-128S""": """https://huggingface.co/facebook/levit-128S/resolve/main/config.json""",
    # See all LeViT models at https://huggingface.co/models?filter=levit
}
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				"""levit"""







   def __init__(     self						:						Dict   ,   lowerCamelCase_						:						Optional[Any]=224   ,   lowerCamelCase_						:						Any=3   ,   lowerCamelCase_						:						List[Any]=3   ,   lowerCamelCase_						:						Dict=2   ,   lowerCamelCase_						:						int=1   ,   lowerCamelCase_						:						List[Any]=16   ,   lowerCamelCase_						:						Any=[128, 256, 384]   ,   lowerCamelCase_						:						Union[str, Any]=[4, 8, 12]   ,   lowerCamelCase_						:						List[Any]=[4, 4, 4]   ,   lowerCamelCase_						:						Dict=[16, 16, 16]   ,   lowerCamelCase_						:						Optional[int]=0   ,   lowerCamelCase_						:						Tuple=[2, 2, 2]   ,   lowerCamelCase_						:						Union[str, Any]=[2, 2, 2]   ,   lowerCamelCase_						:						List[Any]=0.0_2   ,   **lowerCamelCase_						:						Optional[int]   ,   ):





    """simple docstring"""


    super().__init__(**lowerCamelCase_				)
    UpperCamelCase			  =      image_size
    UpperCamelCase			  =      num_channels
    UpperCamelCase			  =      kernel_size
    UpperCamelCase			  =      stride
    UpperCamelCase			  =      padding
    UpperCamelCase			  =      hidden_sizes
    UpperCamelCase			  =      num_attention_heads
    UpperCamelCase			  =      depths
    UpperCamelCase			  =      key_dim
    UpperCamelCase			  =      drop_path_rate
    UpperCamelCase			  =      patch_size
    UpperCamelCase			  =      attention_ratio
    UpperCamelCase			  =      mlp_ratio
    UpperCamelCase			  =      initializer_range
    UpperCamelCase			  =      [
        ["""Subsample""", key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
        ["""Subsample""", key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
    ]





class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase		):
   __lowerCAmelCase           =				version.parse("""1.11"""		)







   @property
   def 						lowerCamelCase_	(     self						:						Any				):





    """simple docstring"""


    return OrderedDict(
        [
            ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
        ]				)







   @property
   def 						lowerCamelCase_	(     self						:						List[str]				):





    """simple docstring"""


    return 1E-4

import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
     import jax
@require_flax
class SCREAMING_SNAKE_CASE_		(      __lowerCAmelCase  ,     unittest.TestCase		):
   __lowerCAmelCase           =				FlaxAutoencoderKL







   @property
   def 						lowerCamelCase_	(     self						:						Tuple				):





    """simple docstring"""


    UpperCamelCase			  =      4
    UpperCamelCase			  =      3
    UpperCamelCase			  =      (32, 32)

    UpperCamelCase			  =      jax.random.PRNGKey(0				)
    UpperCamelCase			  =      jax.random.uniform(lowerCamelCase_   ,   ((batch_size, num_channels) + sizes)				)

    return {"sample": image, "prng_key": prng_key}







   def 						lowerCamelCase_	(     self						:						str				):





    """simple docstring"""


    UpperCamelCase			  =      {
        """block_out_channels""": [32, 64],
        """in_channels""": 3,
        """out_channels""": 3,
        """down_block_types""": ["""DownEncoderBlock2D""", """DownEncoderBlock2D"""],
        """up_block_types""": ["""UpDecoderBlock2D""", """UpDecoderBlock2D"""],
        """latent_channels""": 4,
    }
    UpperCamelCase			  =      self.dummy_input
    return init_dict, inputs_dict
